Deep learning with airlines and weather data

In this recipe, we'll see how to run deep learning models on an airlines dataset.

Getting ready

To step through this recipe, you will need a running Spark Cluster in any one of the following modes: Local, standalone, YARN, Mesos. Include the Spark MLlib package in the build.sbt file so that it downloads the related libraries and the API can be used. Install Hadoop (optionally), Scala, and Java. Also, install Sparkling Water as discussed in the preceding recipe.

How to do it…

1. Please download the dataset from https://github.com/ChitturiPadma/datasets/blob/master/allyears2k_headers.csv. The sample records (with a few columns) in the dataset look like the following:

   

2. Here is the code for loading the airline data and fetching records with the specific destination SFO:

      
         import hex.deeplearning.DeepLearning 
         import hex.deeplearning.DeepLearningModel.DeepLearningParameters 
         import org.apache.spark.{SparkContext, SparkConf...